Update app.py

app.py

@@ -1,3 +1,34 @@
+import torch
+from transformers import pipeline
+from datasets import load_dataset
 import gradio as gr
 
-gr.load("models/openai/whisper-small.en").launch()
+# Setup device
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+# Load the ASR model pipeline
+pipe = pipeline(
+    "automatic-speech-recognition",
+    model="openai/whisper-small.en",
+    chunk_length_s=30,
+    device=device,
+)
+
+# Function to make prediction from audio input
+def transcribe(audio):
+    # Convert Gradio input to the format expected by the ASR pipeline
+    prediction = pipe(audio, batch_size=8)["text"]
+    return prediction
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(source="microphone", type="filepath"),
+    outputs="text",
+    title="Speech to Text with Whisper Model",
+    description="Record your voice and transcribe it to text using OpenAI Whisper model."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch()